The Case of Billy Best: 25 Years Later
Bibliographic record
Abstract
Billy Best was diagnosed with Hodgkin lymphoma in 1994 at age 16 and became well-known when he ran away from home to avoid receiving further chemotherapy. His story became national news when, with the support of his adopted parents, he returned home and opted to use complementary and alternative medicine (CAM) instead of standard chemotherapy and radiation for his cancer treatment. Now 25 years since Billy Best entered the public eye, his story is one that is frequently referenced in pediatrics, bioethics, and other related fields. Here, the authors examine the evolution of various features of this case, including treatment of Hodgkin lymphoma, the interplay between medicine and the media, the role of CAM in pediatric care, navigating entrenched disagreements and how best to integrate adolescents into health care decision-making, and the role of narrative in medical practice. The authors explore the unique role of each of these facets of Billy Best's case, describing how each has or has not changed in the quarter century since that time amid the changing landscape of pediatric health care. Ultimately, although many advances have occurred since Billy Best's time, significant work remains. Additional effort will be required in the future to optimize communication, improve treatment toxicities from Hodgkin lymphoma without decreasing survival, integrate the voice and perspective of adolescents into their treatment decisions, and navigate the roles of CAM and the media in pediatric health care.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".